--- title: "Kai-Wei Chang — papers and cards" description: "Kai-Wei Chang: 2 paper cards in the Research library (2022–2023), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/kai-wei-chang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/kai-wei-chang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Kai-Wei Chang # Kai-Wei Chang 2 paper cards in the Research library · 2022–2023 Kai-Wei Chang wrote 2 of the papers Mova reads, in 2022–2023, most of them on [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/); often with [Anoop Kumar](https://md.research.elamur.ai/free/en/authors/anoop-kumar/), [Aram Galstyan](https://md.research.elamur.ai/free/en/authors/aram-galstyan/), [Kuan-Hao Huang](https://md.research.elamur.ai/free/en/authors/kuan-hao-huang/). [OpenAlex](https://openalex.org/A5087096372) · [ORCID](https://orcid.org/0000-0001-5365-0072) · [**h-index 53**](https://openalex.org/authors/A5087096372) · [16481 citations](https://openalex.org/authors/A5087096372) · [432 works](https://openalex.org/works?filter=author.id:A5087096372) — openalex-snapshot, 2026-10-14 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Kai-Wei+Chang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Kai-Wei+Chang) · [dblp](https://dblp.org/search?q=Kai-Wei+Chang) · [ACL Anthology](https://aclanthology.org/search/?q=Kai-Wei+Chang) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Kai-Wei+Chang) Topics: [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/) 2 ## Papers 1. **[ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation](https://md.research.elamur.ai/free/en/papers/huang-2023-paraamr-large-scale-syntactically-diverse/)** *(2023)* ParaAMR builds about 15 million paraphrase pairs by AMR back-translation. Each source sentence is parsed to an AMR graph; a different node is chosen as the focus (the main assertion); the modified graph is linearised and a sentence is generated from it. Candidates with high perplexity under a language model are… 2. **[Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations](https://md.research.elamur.ai/free/en/papers/huang-2022-unsupervised-syntactically-controlled-paraphrase-generation/)** *(2022)* AMRPG generates a paraphrase that follows a requested syntactic form without any paraphrase pairs. It encodes the input twice: an AMR graph gives a semantic embedding, and the constituency parse gives a syntactic embedding. A decoder learns to reconstruct the input from the two. At test time the syntactic embedding… ## Co-authors (6) - [Anoop Kumar](https://md.research.elamur.ai/free/en/authors/anoop-kumar/) ×2 - [Aram Galstyan](https://md.research.elamur.ai/free/en/authors/aram-galstyan/) ×2 - [Kuan-Hao Huang](https://md.research.elamur.ai/free/en/authors/kuan-hao-huang/) ×2 - [Varun Iyer](https://md.research.elamur.ai/free/en/authors/varun-iyer/) ×2 - I-Hung Hsu - Sriram Venkatapathy ## More papers in the library (25) Pages of the Research library: our summary, the ideas, references and who cites each. - [SWAN: Semantic Watermarking with Abstract Meaning Representation](https://md.research.elamur.ai/free/en/papers/ye-2026-swan-semantic-watermarking-abstract-meaning/) — Ziping Ye, Gourab Dey, Christos Christodoulopoulos, et al. · 2026 - [METAL: A Multi-Agent Framework for Chart Generation with Test-Time Scaling](https://md.research.elamur.ai/free/en/papers/li-2025-metal-multi-agent-framework-chart/) — Bingxuan Li, Yiwei Wang, Jiuxiang Gu, et al. · 2025 - [MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?](https://md.research.elamur.ai/free/en/papers/zhang-2024-mathverse-multi-modal-llm-truly/) — Renrui Zhang, Dongzhi Jiang, Yichi Zhang, et al. · 2024 - [Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2023-chameleon-plug-play-compositional-reasoning/) — Pan Lu, Baolin Peng, Hao Cheng, et al. · 2023 - [MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/) — Pan Lu, Hritik Bansal, Tony Xia, et al. · 2023 - [Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-Step](https://md.research.elamur.ai/free/en/papers/li-2023-symbolic-chain-thought-distillation-small/) — Liunian Harold Li, Jack Hessel, Youngjae Yu, et al. · 2023 - [DEGREE: A Data-Efficient Generation-Based Event Extraction Model](https://md.research.elamur.ai/free/en/papers/hsu-2022-degree-data-efficient-generation-based/) — I-Hung Hsu, Kuan-Hao Huang, Elizabeth Boschee, et al. · 2022 - [Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/lu-2022-dynamic-prompt-learning-policy-gradient/) — Pan Lu, Liang Qiu, Kai-Wei Chang, et al. · 2022 - [Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies](https://md.research.elamur.ai/free/en/papers/dev-2021-harms-gender-exclusivity-challenges-non/) — Sunipa Dev, Masoud Monajatipoor, Anaelia Ovalle, et al. · 2021 - [Societal Biases in Language Generation: Progress and Challenges](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/) — Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al. · 2021 - [Syntax-augmented Multilingual BERT for Cross-lingual Transfer](https://md.research.elamur.ai/free/en/papers/ahmad-2021-syntax-augmented-multilingual-bert-cross/) — Wasi Ahmad, Haoran Li, Kai-Wei Chang, et al. · 2021 - [Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/) — Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al. · 2021 - [Towards Controllable Biases in Language Generation](https://md.research.elamur.ai/free/en/papers/sheng-2020-controllable-biases-language-generation/) — Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al. · 2020 - [Gender Bias in Contextualized Word Embeddings](https://md.research.elamur.ai/free/en/papers/zhao-2019-gender-bias-contextualized-word-embeddings/) — Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al. · 2019 - [Mitigating Gender Bias in Natural Language Processing: Literature Review](https://md.research.elamur.ai/free/en/papers/sun-2019-mitigating-gender-bias-natural-language/) — Tony Sun, Andrew Gaut, Shirlyn Tang, et al. · 2019 - [The Woman Worked as a Babysitter: On Biases in Language Generation](https://md.research.elamur.ai/free/en/papers/sheng-2019-woman-worked-as-babysitter-biases/) — Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, et al. · 2019 - [VisualBERT: A Simple and Performant Baseline for Vision and Language](https://md.research.elamur.ai/free/en/papers/li-2019-visualbert-simple-performant-baseline-vision/) — Liunian Harold Li, Mark Yatskar, Da Yin, et al. · 2019 - [Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods](https://md.research.elamur.ai/free/en/papers/zhao-2018-gender-bias-coreference-resolution-evaluation/) — Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al. · 2018 - [Generating Natural Language Adversarial Examples](https://md.research.elamur.ai/free/en/papers/alzantot-2018-generating-natural-language-adversarial-examples/) — Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, et al. · 2018 - [Learning Gender-Neutral Word Embeddings](https://md.research.elamur.ai/free/en/papers/zhao-2018-learning-gender-neutral-word-embeddings/) — Jieyu Zhao, Yichao Zhou, Zeyu Li, et al. · 2018 - [Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints](https://md.research.elamur.ai/free/en/papers/zhao-2017-men-also-like-shopping-reducing/) — Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al. · 2017 - [Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings](https://md.research.elamur.ai/free/en/papers/bolukbasi-2016-man-computer-programmer-woman-homemaker/) — Tolga Bolukbasi, Kai-Wei Chang, James Zou, et al. · 2016 - [A Joint Framework for Coreference Resolution and Mention Head Detection](https://md.research.elamur.ai/free/en/papers/peng-2015-joint-framework-coreference-resolution-mention/) — Haoruo Peng, Kai-Wei Chang, Dan Roth · 2015 - [A Constrained Latent Variable Model for Coreference Resolution](https://md.research.elamur.ai/free/en/papers/chang-2013-constrained-latent-variable-model-coreference/) — Kai-Wei Chang, Rajhans Samdani, Dan Roth · 2013 - [Inference Protocols for Coreference Resolution](https://md.research.elamur.ai/free/en/papers/chang-2011-inference-protocols-coreference-resolution/) — Kai-Wei Chang, Rajhans Samdani, Alla Rozovskaya, et al. · 2011